MLOps Engineer (f/m/div.)
Trabalho remoto
Híbrido
Áreas de trabalho
Engenharia
Junta-te enquanto
Profissional
Data de início
Mediante acordo
Horário de trabalho
Tempo inteiro
Divisão
Cross-Domain Computing Solutions
As tuas tarefas
MLOps Strategy & Architecture
- Contribute to the definition and evolution of the MLOps strategy for a hybrid cloud environment, ensuring alignment with business objectives, security standards, and industry best practices;
- Support the design of a scalable MLOps platform with a self-service approach, covering the full ML lifecycle, including data ingestion, feature engineering, model training, validation, deployment, and monitoring;
- Develop and maintain clear and structured documentation for MLOps processes, workflows, and infrastructure.
Hybrid ML Lifecycle Implementation
- Design and implement Infrastructure as Code (IaC) solutions using Terraform to provision and manage cloud and on-premises resources;
- Ensure robust security practices to protect sensitive data and ML models across hybrid environments;
- Develop and deploy new platform functionalities while ensuring key non-functional requirements, particularly reproducibility and reliability;
- Build and maintain monitoring dashboards and alerting systems to proactively detect and resolve platform issues.
Collaboration & Contribution
- Collaborate closely with ML engineers, data scientists, software engineers, and infrastructure teams to deliver a scalable and high-quality MLOps platform;
- Communicate effectively with both technical and non-technical stakeholders, ensuring alignment and transparency;
- Stay up to date with emerging MLOps trends, tools, and technologies, actively contributing to continuous improvement;
- Participate in code reviews and contribute to the definition and adoption of best practices.
O teu perfil Education:
- MSc or Ph.D. in Software Engineering, Computer Science, Data Science, Machine Learning or a related field.
Experience:
- 2+ years of experience in MLOps, Data Engineering, DevOps, or similar roles.
Technical Skills:
- Good Understanding of the ML development process and model life cycle;
- Good understanding of DevOps principles and practices;
- Experience designing, implementing, integrating, and maintaining MLOps solutions or CI/CD pipelines;
- Good scripting and automation skills with Python and Bash;
- Knowledge of Cloud solutions, preferably Azure;
- Basic understanding of Terraform, GitHub Actions, and Kubernetes;
- Experience with GNU/Linux systems as key development environment.
Soft Skills:
- Excellent problem-solving skills;
- Effective communication skills, team player, and capable of collaborating across functional areas;
- Proactive, customer and result-oriented personality;
- Fluent in English, written and spoken;
- Experience working in Agile/SAFe environments.
Education:
- MSc or Ph.D. in Software Engineering, Computer Science, Data Science, Machine Learning or a related field.
Experience:
- 2+ years of experience in MLOps, Data Engineering, DevOps, or similar roles.
Technical Skills:
- Good Understanding of the ML development process and model life cycle;
- Good understanding of DevOps principles and practices;
- Experience designing, implementing, integrating, and maintaining MLOps solutions or CI/CD pipelines;
- Good scripting and automation skills with Python and Bash;
- Knowledge of Cloud solutions, preferably Azure;
- Basic understanding of Terraform, GitHub Actions, and Kubernetes;
- Experience with GNU/Linux systems as key development environment.
Soft Skills:
- Excellent problem-solving skills;
- Effective communication skills, team player, and capable of collaborating across functional areas;
- Proactive, customer and result-oriented personality;
- Fluent in English, written and spoken;
- Experience working in Agile/SAFe environments.
